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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,153 records · Page 64
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

LETID in Legacy and Modern PV Modules: Accelerated Testing and Field Deployment

The kinetics of light- and elevated temperature-induced degradation (LETID) in silicon solar cells depend on the precise operating excess carrier density (?n) of the device. This dependency causes differences in the way LETID manifests in modern, higher-efficiency devices compared to lower-efficiency, legacy devices that might have been deployed in the field in previous years. In this work we model how different vintages of devices are expected to behave in both accelerated laboratory testing, as well as field deployment. The differing excess carrier densities encountered in various module vintages has implications both for interpreting accelerated test data, as well as identifying, diagnosing, and potentially treating LETID in the field.

excess carrier density↗
DOE OSTI2023

Ground Motion Models (GMMs) Improvements Using Earthquake Simulations on High Performance Computers

A computationally efficient simulation platform was developed that can provide representative synthetic ground motions from crustal earthquakes in the Stable Continental Regions of Central and Eastern US (CEUS), using 3D modeling and high-performance computing. The main objective was to use synthetic ground motion to provide constrains to refinements of exiting ergodic Ground Motion Models (GMMs), for large magnitude earthquakes and near-fault distances, for which these models are less reliable. Physics-based broadband (0-5Hz) ground motion simulations were used to estimate the near-fault ground motion amplitudes and within event and between-event variabilities associated with fault rupture characteristics. As part of a strategy for selecting a reginal velocity model and validation of developed rupture modeling technique, ground motions from the moment magnitude Mw5.0 November 7, 2016, Cushing Oklahoma, and Mw5.8 September 3, 2016, Pawnee Oklahoma earthquakes were simulated. In our simulations we used a 3D regional velocity model that was based on Saikia’s 1D velocity model. Saikia’s model demonstrated better performance in modelling high frequency regional wave propagation for CEUS region. The proposed 3D model includes lateral variations added to the 1D background model using the stochastic scheme of Pitarka and Mellors. Comparisons of the simulations with recordings of both earthquakes demonstrated the reliability of our deterministic simulation approach while emphasizing the importance of including small-scale variability in the regional velocity model needed to reproduce the observed high-frequency wave scattering effects. As part of validation analysis, comparisons with different GMMs for a Mw6.5 earthquake in the CESUS region resulted in a very good match between the simulated and empirical ground motion models. Initial investigations of within-event and between-event ground motion variabilities for Mw6.5 scenario earthquakes on a strike-slip fault, suggest that they are strongly related to spatial slip and slip rate variations, average rupture velocity, rupture area and rupture initiation location. For certain scenarios we found that the ground motion variability observed at near-fault distances (< 5 km) also persists at longer distances. Regardless of the rupture scenario, the simulated ground motion tends to fully saturate at short distances and for all periods. The near-fault saturation has to do with the attenuation of waves propagating along the fault and local rupture radiation pattern that also contribute to stronger ground motion variation at such distances. Analysis of effects of rupture initiation location suggest that the peak ground motion (PGV) and spectral acceleration (SA) can be quite variable due to rupture directivity effects. Such effects are stronger at periods longer than 1s. The effect of the 1D velocity models and surface topography on simulated ground motion were investigated by comparing three component synthetic seismograms computed at selected sites. Effect of surface topography was considered using the ratio between spectral accelerations simulated for two 1D models with flat surface topography and realistic model with surface topography. Overall, the topography slightly amplifies (by ~30%) the ground motion amplitude in the frequency range 1-3Hz. The effect of topography is more visible in the surface and coda waves portion of the seismograms.

58 GEOSCIENCES↗
DOE OSTI2021

Cytochrome Nanowire XRD

Microbial metabolism plays an important role in the global cycling of carbon, nutrients, and metals. Recent discovery of microorganisms sharing energy using direct electrical connections might represent a prominent strategy by which anaerobic microorganisms interact with the diversity of environments. The purpose of the proposed research is to apply these newly developed principles of electron exchange in microbial communities to the study of biogeochemical cycling in climate and subsurface systems. Previous studies revealed that soil bacteria Geobacter sulfurreducens produce conductive pili nanofilaments that facilitate long-range electron transport to extracellular electron acceptors and other cells. This discovery has already transformed our understanding of the function of microbial communities in diverse environments, making basic contributions to microbial ecology and helping to improve practical applications such as increasing current output of microbial fuel cells and enhancing the conversion of organic waste to methane. Microbial electron exchange via pili may also contribute to methane production in terrestrial environments that are major sources of atmospheric methane. However, the mechanism of electron transport through pili is not well understood. Initial studies have suggested that pili exhibit metallic-like conductivity similar to conducting polymer polyaniline. However, these studies were limited to electrical measurements. X-ray diffraction studies have suggested that aromatic amino acids tyrosine and phenylalanine are closely packed in pili. But these studies used homology modeling to predict the pilus assembly and information about the number of monomers in each pilus assembly unit and their organization are still lacking. The central hypothesis of this proposal is aromatics in pili enable intermolecular electron delocalization due to pi-stacking that can give rise to metallic-like conductivity. By analyzing pili structure using infrared scattering-scanning near field optical microscope (IR s-SNOM) and combining with solution NMR, Focused Ion Beam (FIB and computational capabilities, this work will provide comprehensive understanding of the conduction mechanism from a structure-function perspective. The specific aims are: 1) With infrared scattering scanning near field optical microscope (IR s-SNOM), image the organization and density of pilin monomers and pH-induced conformational changes in a pilus filament. 2) With solution NMR, resolve pH-induced structural changes in the pilin monomer. 3) Using Focused Ion Beam (FIB), draw electrodes on single pili to measure their conductivity. 4) With computational modeling using the NWChem, simulate the effect of environment on the electronic properties of pili as a function of pH. The proposed work will gain the nanoscale insight into the structure of the pili, as the basis for understanding interspecies electrical communications. The improved understanding will be harnessed to accelerate bioenergy production and bioremediation using pili as well as for predictive modeling of carbon cycling in diverse environments to reach the central goals of DOE-BER to develop sustainable energy sources, regulate the contaminants in the subsurface and understand the effects of greenhouse gas emissions on biosphere. The proposed studies will provide design principles for engineering of electrical interactions among these communities by manipulating the amino acid composition of pili. Moreover, these studies will identify the forces that maintain the function of these communities in the face of environmental perturbation. Therefore, these studies will help to address the need "to incorporate process understanding of biogeochemical cycling into a scalable hierarchy of predictive capabilities" specified in EMSL's Science Themes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Online Modelling and Optimization of Nonlinear Integrable Systems

Nonlinear integrable optics was recently proposed as a design approach to increase the limits on beam brightness and intensity imposed by fast collective instabilities. To study these systems experimentally, a new research electron and proton storage ring, the Integrable Optics Test Accelerator, was constructed and recently commissioned at Fermilab. Beam-based diagnostics and online modelling of nonlinear systems presents unique challenges - in this paper, we report on our efforts to develop optimization methods suited for such lattices. We explore the effectiveness of neural networks as fast online surrogate estimators, and integrate them into a beam-based tuning algorithm. We also develop a method of knob dimensionality reduction and subsequent robust multivariate optimization for maximizing key performance metrics under complicated lattice optics constraints.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

NEML2 - THE NEW ENGINEERING MATERIAL MODEL LIBRARY, VERSION 2

SF-22-157 NEML2 is an extension of an earlier open source code developed at ANL (SF-xxxx) called NEML. These libraries provide tools for constructing and using models of engineering materials, with a focus on high temperature materials for nuclear reactor applications. The software include tools for setting up material models, calibrating models, storing models for later use in other simulations, and running simple "material point" simulations of the material behavior. The main difference between NEML and NEML2 is the new software has been complete restructured to run on GPUs and other accelerators in order to improve the performance of methods used to train constitutive models against data and to improve the performance of the final models in production environments, like finite element software. While over time we expect NEML2 to become more-or-less feature complete with NEML we are filing a new software disclosure because (1) the library has been complete restructured and (2) we want to host NEML2 in a separate repository.

MESSNER, MARK↗
DOE OSTI2022

ExaAM: Metal additive manufacturing simulation at the fidelity of the microstructure

Additive manufacturing (AM), or 3D printing, of metals is transforming the fabrication of components, in part by dramatically expanding the design space, allowing optimization of shape and topology. However, although the physical processes involved in AM are similar to those of welding, a field with decades of experimental, modeling, simulation, and characterization experience, qualification of AM parts remains a challenge. The availability of exascale computational systems, particularly when combined with data-driven approaches such as machine learning, enables topology and shape optimization as well as accelerated qualification by providing process-aware, locally accurate microstructure and mechanical property models. We describe the physics components comprising the Exascale Additive Manufacturing simulation environment and report progress using highly resolved melt pool simulations to inform part-scale finite element thermomechanics simulations, drive microstructure evolution, and determine constitutive mechanical property relationships based on those microstructures using polycrystal plasticity. We report on implementation of these components for exascale computing architectures, as well as the multi-stage simulation workflow that provides a unique high-fidelity model of process–structure–property relationships for AM parts. In addition, we discuss verification and validation through collaboration with efforts such as AM-Bench, a set of benchmark test problems under development by a team led by the National Institute of Standards and Technology.

3D printing↗
DOE OSTI2024

Generating An Advanced Cross-section Library For HTGR Pebble Bed Depletion Calculations Using Reduced-Order Model Generation Techniques

For code development, Advanced Reactor Technologies - Gas Cooled Reactors Program (ART-GCR) rely on a collaboration with the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, but the cross sections generation and the methodology definition is part of this program area goals. Based on previous studies in FY23, the size of microscopic cross section libraries increases rapidly with the number of tabulations, requiring significant amount of memory and drastically slowing down the Griffin calculations when evaluating cross sections via the multivariate linear interpolation approach. Rising to these challenges, this work investigates constructing Reduced-order Models (ROMs) for the multi-group microscopic cross sections to accelerate the cross section evaluation in Griffin. A database of multigroup cross sections is first collected considering all possible parameters that a designer could change for optimization. Down-selection of the ROM techniques afterward shows Deep Neural Network (DNN) as the best candidate when jointly consider memory efficiency, predictive accuracy, computational cost, scalability, flexibility and ease of implementation of the algorithms in comparison to the multidimensional interpolation. This work develops a specific interface that enables the cross section predictions using pre-trained DNN models into Griffin leveraging the existing ROM capabilities. DNNs have been trained for all isotopes for use in Griffin. Preliminary Griffin testing shows that DNNs exhibit exceptional predictive accuracy and the use of DNNs provides orders of magnitude improvement in memory efficiency compared to conventional interpolation techniques. With such ROM techniques, it holds great promise to further increase the fidelity of the Pebble Bed Reactor (PBR) simulation by increasing the number of tabulations/state variables during cross section evaluation, while maintaining the computational cost affordable in Griffin.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Fuel/Basket Degradation Modeling Summary

This report documents the activities in a preliminary phase of development for three models: 1) waste package breach model, 2) fuel/basket degradation model, and 3) dual-purpose canister (DPC) crush model. The waste package breach model describes the coupling of mass flow, heat transport, and canister shell deformation in response to a heat-generating (criticality) event. The fuel/basket degradation model describes potential weakening and disaggregation of the DPC structure from corrosion, possibly accelerated by seismic ground motion. Progressively degraded three-dimensional (3D) configurations of the fuel, basket, and shell are generated for future analysis of reactivity (with as-loaded DPC fuel characteristics). Another important application for the fuel/basket degradation model is validation of the two stylized degradation cases currently being used by other investigators for analysis of the as-loaded DPC inventory under disposal conditions. The DPC crush model investigates stability of a typical DPC after breach of the disposal overpack allows fluids from the repository near-field environment to penetrate and externally pressurize the canister shell. Preliminary results show that large deformation of the DPC could occur for external pressure on the order of 10 to 15 MPa, or the shell could be stable (not collapse) with pressure of 20 MPa or greater if the basket plates are fully welded at the connections.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Enhanced Catalyst Durability and Sulfur Tolerance by Atomic Layer Deposition (CRADA Final Report)

This CRADA advanced the use of atomic layer deposition (ALD) catalyst coatings to improve sulfur tolerance and demonstrate improved catalyst durability for biomass conversion chemistries. This project leveraged National Laboratory and industry expertise for ALD catalyst coating development between NREL, ALD NanoSolutions, Inc. ("ALD NanoSolutions"), and Johnson Matthey PLC ("Johnson Matthey"). To better understand the role of ALD coatings on catalyst activity and durability, a joint experimental and computational effort combined bench-scale ALD catalyst synthesis, material characterization, catalyst testing, and modeling of catalyst surface energetics. In addition, to demonstrate the commercial relevance of this technology, scaled ALD coated catalysts were subjected to continuous testing and accelerated aging to validate performance gains. Results were used to inform ALD catalyst coating manufacturing cost models, as well as biobased chemical process cost models.

09 BIOMASS FUELS↗
DOE OSTI2025

Benders Decomposition Using Graph Modeling and Multi-Parametric Programming

Benders decomposition is a widely used method for solving large and structured optimization problems, but its performance is affected by the repeated solution of subproblems. We propose a flexible and modular algorithmic framework for accelerating Benders decomposition. Specifically, we express the problem structure by using a graph-theoretic modeling abstraction in which nodes represent optimization subproblems and edges represent connectivity between subproblems. A key innovation of our approach is that we embed multiparametric programming (mp) surrogates for node subproblems, which maps the exact analytical map of the subproblem solution space. The use of mp surrogates allows us to replace subproblem solves with fast look-ups and function evaluations for primal and dual variables during the iterative Benders process. We formally show the equivalence between classical Benders cuts and those derived from the mp solution. We implement our framework in the open-source PlasmoBenders.jl software package. To demonstrate the capabilities of the proposed framework, we apply it to a two-stage stochastic programming problem, which aims to make optimal capacity expansion decisions under market uncertainty. We evaluate both single-cut and multicut variants of Benders decomposition and show that the use of mp surrogates achieves substantial speedups in subproblem solve time, while preserving the convergence guarantees of Benders decomposition. We highlight advantages in solution analysis and interpretability that is enabled by mp critical region tracking; specifically, we show that these reveal how decisions evolve geometrically across the Benders search. Our results aim to demonstrate that combining surrogate modeling with graph modeling offers a promising and extensible foundation for structure-exploiting decomposition. In addition, by decomposing the problem into more tractable subproblems, the proposed approach also aims to overcome scalability issues of mp. Finally, the use of mp surrogates provides a unifying and modular optimization framework that enables the representation of heterogeneous node subproblems as modeling objects with a homogeneous structure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Coupling Noah-Multiparameterization land-surface Model with Energy Research and Forecasting Model

The Energy Research and Forecasting (ERF) model is a high-performance atmospheric model built on the AMReX adaptive mesh refinement (AMR) framework, enabling efficient simulations on heterogeneous computing platforms that combine multicore processors with hardware accelerators. To support land–atmosphere interactions within ERF’s AMR-based environment, a land-surface model must be capable of operating directly on hierarchically refined meshes. In this work, we present a methodology for coupling the Fortran-based Noah-Multiparameterization (Noah-MP) land-surface model with ERF’s C++ codebase. Rather than rewriting Noah-MP, we construct a Fortran–C interoperability layer using CodeScribe, a tool that leverages large language models (LLMs) to automate the generation of interface code. CodeScribe applies structured prompting techniques to generate bindings that support efficient data exchange and function calls between ERF and Noah-MP. The coupling framework also incorporates AMR-aware data handling strategies, allowing NoahMP to operate seamlessly within ERF’s hierarchical mesh structure. This work provides a structured approach for integrating legacy Fortran models into modern C++-based modeling systems using LLM-assisted code generation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Validating methods for modeling composition gradients in planar shock experiments

An interface is Rayleigh–Taylor (RT) unstable when acceleration pushes a less dense material into a more dense one, and the growth of the instability is governed partly by the Atwood number gradient. Double-shell inertial confinement fusion capsules have a foam spacer layer pushing on an inner capsule composed of a beryllium tamper and high-Z inner shell, and so have RT unstable interfaces that require benchmarking. To this end, the results of a planar shock experiment with beryllium/tungsten targets are presented. One target had the normal bilayer construction of beryllium and tungsten in two distinct layers; the second target had the beryllium grading into tungsten with a quasi-exponential profile, motivated by the potential for reduced RT growth with the gradient profile. Simulations mimic the shock profiles for both targets and match the shock velocity to within 5%. These results validate the ability of our simulations to model double-shell capsules with bilayer or graded layer Be/W inner shells, which are needed to design future experiments at the National Ignition Facility.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Accelerate microstructure evolution simulation using graph neural networks with adaptive spatiotemporal resolution

Abstract Surrogate models driven by sizeable datasets and scientific machine-learning methods have emerged as an attractive microstructure simulation tool with the potential to deliver predictive microstructure evolution dynamics with huge savings in computational costs. Taking 2D and 3D grain growth simulations as an example, we present a completely overhauled computational framework based on graph neural networks with not only excellent agreement to both the ground truth phase-field methods and theoretical predictions, but enhanced accuracy and efficiency compared to previous works based on convolutional neural networks. These improvements can be attributed to the graph representation, both improved predictive power and a more flexible data structure amenable to adaptive mesh refinement. As the simulated microstructures coarsen, our method can adaptively adopt remeshed grids and larger timesteps to achieve further speedup. The data-to-model pipeline with training procedures together with the source codes are provided.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Accelerating Combustion and Surface Chemistry Simulations

Design of modern combustion systems relies on computer models to predict how changes in design will affect performance. These models have largely displaced previous methods that rely on the designer’s intuition or costly and time-consuming physical testing. By using improved models, design cycles can be shortened, and cleaner and more efficient combustion devices can be created. This project aims to improve computer simulations of transportation fuels with the goal of making these simulations faster and more accurate for predicting combustion in vehicles.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Modular cell-free expression plasmids to accelerate biological design in cells

Industrial biotechnology aims to produce high-value products from renewable resources. This can be challenging because model microorganisms—organisms that are easy to use like Escherichia coli—often lack the machinery required to utilize desired feedstocks like lignocellulosic biomass or syngas. Non-model organisms, such as Clostridium, are industrially proven and have desirable metabolic features but have several hurdles to mainstream use. Namely, these species grow more slowly than conventional laboratory microbes, and genetic tools for engineering them are far less prevalent. To address these hurdles for accelerating cellular design, cell-free synthetic biology has matured as an approach for characterizing non-model organisms and rapidly testing metabolic pathways in vitro. Unfortunately, cell-free systems can require specialized DNA architectures with minimal regulation that are not compatible with cellular expression. In this work, we develop a modular vector system that allows for T7 expression of desired enzymes for cell-free expression and direct Golden Gate assembly into Clostridium expression vectors. Utilizing the Joint Genome Institute’s DNA Synthesis Community Science Program, we designed and synthesized these plasmids and genes required for our projects allowing us to shuttle DNA easily between our in vitro and in vivo experiments. We next validated that these vectors were sufficient for cell-free expression of functional enzymes, performing on par with the previous state-of-the-art. Lastly, we demonstrated automated six-part DNA assemblies for Clostridium autoethanogenum expression with efficiencies ranging from 68% to 90%. We anticipate this system of plasmids will enable a framework for facile testing of biosynthetic pathways in vitro and in vivo by shortening development cycles.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

DarkNews: a Python-based event generator for heavy neutral lepton production in neutrino-nucleus scattering

We introduce DarkNews, a lightweight Python-based Monte-Carlo generator for beyond-the-Standard-Model neutrino-nucleus scattering. The generator handles the production and decay of heavy neutral leptons via additional vector or scalar mediators, as well as through transition magnetic moments. DarkNews samples pre-computed neutrino-nucleus upscattering cross sections and heavy neutrino decay rates to produce dilepton and single-photon events in accelerator neutrino experiments. We present two case studies with differential distributions for models that can explain the MiniBooNE excess. The aim of this code is to aid the neutrino theory and experimental communities in performing searches and sensitivity studies for new particles produced in neutrino upscattering.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

An Analytical Model of Erosive Wear of BioMass Comminution Components

An analytical erosion model that relates critical process parameters (speed and impingement angle) to critical material attributes of inorganic mineral species in feedstock (density, size, aspect ratio) and substrate (hardness, toughness, and fatigue ductility) was applied to model wear in pretreatment milling operations. Results of the model were compared to experimental measurements of wear produced using the Accelerated Wear Test (AWT) rig at Idaho National Laboratory (INL). Results showed that there is good agreement between predicted and measured performance, and that a quality-by-design (QbD) tool can be developed to predict component reliability based on scientific engineering principles in lieu of trial-and-error approaches.

09 BIOMASS FUELS↗